1. Field of the Invention
The present invention relates to a detection method and an algorithm, particularly to an object-detection method, which can process objects having multiple classes of appearances, and a Multi-class Bhattacharyya Boost (MBH-Boost) algorithm used therein.
2. Description of the Related Art
To integrate the digital image processing technology with automatic monitoring/control, building security, or man-machine interaction is an active field the academic circle and the industry endeavor to study and develop. Various achievements thereof will enable automatic processes to replace some human works. Among this field, object detection is a critical preprocessing because it is only after the system has known the positions of target objects that the succeeding processes, such as identifying human faces or other objects in a security system, or monitoring/tracing human beings or vehicles in a monitoring/control system, can be executed. Therefore, object-detection technology has universal utility. And, some objective and measurable factors, such as detection speed, detection accuracy and detection robustness, can be used to evaluate the performance of a detection algorithm.
Recently, the learning mechanism of a boosting algorithm has been often used in object detection, and it can also be integrated with a cascade framework to increase detection speed. The efficiency and accuracy of the object-detection technology based on the boosted cascade has acquired general attention in academic circles, and further researches are also being undertaken, for example, determining the interference factors in detecting human faces, such as illumination, occlusion and rotation angles, and promoting detection accuracy under the influence of a variety of extrinsic factors.
In resolving those discussed above, the present invention proposes an object-detection method and a multi-class Bhattacharyya Boost algorithm used therein to overcome the problems.